Seminar · Computational Neuroscience
Population coding in the cerebellum: a machine learning perspective
Reza Shadmehr · Johns Hopkins School of Medicine
Wed, Apr 6, 2022 · 15:00 UTC
The cerebellum resembles a feedforward, three-layer network of neurons in which the “hidden layer” consists of Purkinje cells (P-cells) and the output layer consists of deep cerebellar nucleus (DCN) neurons. In this analogy, the output of each DCN neuron is a prediction that is compared with the actual observation, resulting in an error signal that originates in the inferior olive. Efficient learning requires that the error signal reach the DCN neurons, as well as the P-cells that project onto them. However, this basic rule of learning is violated in the cerebellum: the olivary projections to